Using a wide range of operational research (OR) optimization examples, Applied Operational Research with SAS demonstrates how the OR procedures in SAS work. The book is one of the first to extensively cover the application of SAS procedures to OR problems, such as single criterion optimization, project management decisions, printed circuit board assembly, and multiple criteria decision making.

The text begins with the algorithms and methods for linear programming, integer linear programming, and goal programming models. It then describes the principles of several OR procedures in SAS. Subsequent chapters explain how to use these procedures to solve various types of OR problems. Each of these chapters describes the concept of an OR problem, presents an example of the problem, and discusses the specific procedure and its macros for the optimal solution of the problem. The macros include data handling, model building, and report writing.

While primarily designed for SAS users in OR and marketing analytics, the book can also be used by readers interested in mathematical modeling techniques. By formulating the OR problems as mathematical models, the authors show how SAS can solve a variety of optimization problems.

"... the authors do a good job of explaining how to apply SAS to a wide variety of problems in operations research and operations management, and the publisher makes copies of SAS code from the book available to purchasers of the book. For the reader who has a sufficient background in operations research, is comfortable with SAS macros, and is interested in learning, this book will provide a welcome and useful resource."-The American Statistician, August 2014

"This book successfully bridges the gap between theory and practice. Written primarily for SAS, the authors present a wide range of optimisation problems to demonstrate how the SAS/OR (R) procedures work. The text is well written, easy to follow, and will appeal both to those who have an interest only in concepts and to those merely interested in solving practical problems."-Carl M. O'Brien, International Statistical Review (2013), 81

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